Technoeconomic Assessment and Robust Validation of Hydropower Expansion Pathways under Deep Uncertainty: A Case Study of the Expansion of Bumbuna Hydroelectric Power in Sierra Leone

Energy planning under uncertainty remains a critical challenge in developing economies, where data limitations and climate variability complicate long, term investment decisions. In Sierra Leone, these challenges are particularly acute given low electricity access 36% and heavy reliance on hydropower with strong seasonal variability. This study addresses the limitations of deterministic energy modelling, which typically assumes perfect foresight and produces single optimal pathways that may not remain valid under uncertain futures. To overcome this, we integrate an OSeMOSYS, based technoeconomic optimization model with a Robust Decision Making (RDM) framework to evaluate resilient energy strategies. The approach is applied to the case of the Bumbuna Hydroelectric Expansion, including the proposed upstream Yiben reservoir. Key contributions include the systematic validation of least, cost model outputs under deep uncertainty through hundreds of parameter variations, and the identification of critical uncertainty drivers using scenario discovery techniques (PRIM). Results show that scenarios incorporating the Yiben reservoir (Scenarios 6 and 7) achieve up to ,100% renewable electricity generation by 2030, reduce reliance on heavy fuel oil generation, and deliver lower system costs and Levelised Cost of Electricity compared to alternatives without storage expansion. Furthermore, these scenarios consistently demonstrate robustness across a wide range of futures, clustering in low, cost, high, renewable outcome spaces. The findings highlight hydropower storage as a key enabler of system reliability and decarbonization. From a policy perspective, the study underscores the importance of integrating uncertainty analysis into national energy planning and supports prioritising cascade hydropower development to enhance energy security